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Second Opinion® BLE is a radiological automated image processing software device intended to identify and display bone level measurements in bitewing and periapical radiographs. It should not be used in lieu of full patient evaluation or solely relied upon to make or confirm a diagnosis.
It is designed to aid dental health professionals to review bitewing and periapical radiographs of permanent teeth in patients 12 years of age or older as a concurrent and second reader.

Second Opinion BLE is a radiological automated image processing software device intended to identify and display bone level measurements in bitewing and periapical radiographs. It should not be used in lieu of full patient evaluation or solely relied upon to make or confirm a diagnosis.
It is designed to aid dental health professionals to review bitewing and periapical radiographs of permanent teeth in patients 12 years of age or older as a concurrent and second reader.
Second Opinion BLE consists of three parts:

• Application Programing Interface ("API")
• Machine Learning Modules ("ML Modules")
• Client User Interface (UI) ("Client")
  The processing sequence for an image is as follows:

1. Images are sent for processing via the API
2. The API routes images to the ML modules
3. The ML modules produce detection output
4. The UI renders the detection output
   The API serves as a conduit for passing imagery and metadata between the user interface and the machine learning modules. The API sends imagery to the machine learning modules for processing and subsequently receives metadata generated by the machine learning modules which is passed to the interface for rendering.
   Second Opinion BLE uses machine learning to detect bone level measurements. Images received by the ML modules are processed yielding detections which are represented as metadata. The final output is made accessible to the API for the purpose of sending to the UI for visualization. Detected bone level measurements are displayed as linear overlays atop the original radiograph which indicate to the practitioner which regions contain which detected potential conditions that may require clinical review. The clinician can toggle over the image to highlight a potential condition for viewing.

Here's a detailed breakdown of the acceptance criteria and the study proving the device meets them, based on the provided FDA clearance letter for Second Opinion® BLE:

Acceptance Criteria and Reported Device Performance

Study Details

2. Sample Sizes Used for the Test Set and Data Provenance

• Test Set Sample Size: 396 subjects, yielding 229 bitewing radiographs and 167 periapical radiographs.
• Data Provenance: Retrospective clinical subject data. The country of origin is not explicitly stated, but the use of "US licensed dentists" and "U.S. Dental Radiologists" suggests a US-centric data source.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

• Number of Experts: 3 for initial labeling, plus 2 for adjudication. In total, 5 experts were involved in establishing ground truth.
• Qualifications of Experts:
  • Initial Labeling: Three US licensed dentists.
  • Adjudication: Two U.S. Dental Radiologists.
  • Specific experience (e.g., "10 years of experience") is not provided.

4. Adjudication Method for the Test Set

• Adjudication Method: Divergent measurements (clinically significant differences) from the initial three dentists were then adjudicated by two U.S. Dental Radiologists. This appears to be a 3+2 (initial + adjudication) method for establishing ground truth for conflicting cases.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

• MRMC Study: No, the provided text describes a standalone performance assessment to validate the clinical usefulness of the added bone level measurement tool. It does not mention a comparative effectiveness study involving human readers with and without AI assistance to measure improvement. The statement "All devices have undergone clinical studies which demonstrate statistically significant improvement in aided reader performance" in section 8 refers to all devices (including predicate/reference), but the details provided for Second Opinion® BLE's clinical test (section 12) specifically describe a standalone validation.

• Effect Size: Not applicable, as an MRMC comparative effectiveness study was not detailed for the subject device.

6. If a Standalone (algorithm only without human-in-the-loop performance) was done

• Standalone Study: Yes. The clinical evaluation was performed as a "standalone performance assessment" of the Second Opinion BLE software. The reported precision and recall values, and the mean absolute difference, directly reflect the algorithm's performance against the established ground truth.

7. The Type of Ground Truth Used

• Type of Ground Truth: Expert consensus with adjudication. The ground truth was established by three US licensed dentists, with divergent measurements adjudicated by two U.S. Dental Radiologists (refer to #3 and #4). This is referred to as "GT Second Opinion BLE" in the performance results.

8. The Sample Size for the Training Set

• Training Set Sample Size: The document does not provide the sample size for the training set. It only mentions that the technology "Utilizes computer vision neural network algorithms, developed from open-source models using supervised machine learning techniques."

9. How the Ground Truth for the Training Set was Established

• Training Set Ground Truth Establishment: The document does not explicitly state how the ground truth for the training set was established. It only mentions that the algorithms were "developed from open-source models using supervised machine learning techniques," which implies that the training data and their corresponding ground truth labels were used in a supervised manner.

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